Job Board

Lab Summary
We are NEON, a subsidiary of Samsung dedicated to creating Artificial Humans who interact with you in ways indistinguishable from the real world. Our NEONs (Neo humaNs) draw inspiration from the most natural of interfaces: interaction with another human being. Bringing together a world-class R&D team of researchers, developers, and engineers, that are building production technology at the cutting edge of artificial intelligence, machine learning, real-time computing, conversational agents, computer graphics, design, and more.

NEONs hold the potential to advance our digital world while preserving the elements of human interaction that are meaningful to all of us. If you share that dream – if you want to make the visions you saw in Her, Blade Runner, and more into tangible reality – and are passionate about taking such ideas into handcrafted renderings, we would love to hear from you!

Position Summary
We are seeking collaborative and exploration-minded researchers with both strong experience and a keen interest in taking fundamental research into new product innovation. We expect our researchers to understand the state of the art, and the push past that boundary by working together to distill and apply insights into application. As part of our team, you will both guide research and play a key role in developing and scaling the technology for a wide user base. Our team is based in Mountain View, California. However, remote work is negotiable for this position!

Responsibilities
Research, design, and develop novel algorithms in the emerging area of artificial humans.
Define the success metric and conduct experiments to validate these algorithms in a production environment.
Work with engineering and product leaders to help identify and prioritize new research opportunities.
Collaborate with world-class research institutes inside and outside Samsung to advance the state of the art in the field.
Share your research with the community in the form of patents and publications at top-tier venues.

Requirements
Ph.D. in Computer Vision, Computer Graphics, Machine Learning or a related field or equivalent practical experience and training
Deep knowledge and hands on expertise in at least one of these areas:
Generative modeling for images and videos, human face and gesture modeling, neural rendering, or related techniques
Modeling, analyzing, and synthesizing human emotions, behavior, expressions, or gestures
Capture, estimation, and tracking of human facial expressions or body shape & pose
Geometric computer vision, object or scene understanding, multi-view geometry
Strong publications record at top-tier research venues such as CVPR, ICCV, ECCV, NeurIPS, ICLR, AAAI or SIGGRAPH
Ability to write efficient, clean, and reusable code in Python
Fluent in one of the popular Deep Learning frameworks such as Pytorch or Tensorflow

A Little Extra!
Prior experience in commercializing machine learning research into a product
Ability to write efficient and clean code in C++

We have a postdoc opening on developing Arabic handwritten text recognition systems at the NC State University, North Carolina, USA.

No Arabic knowledge is needed but please make sure that you are good at deep learning and you are in one of the following fields: document analysis, computer vision, and image processing. You will be jointly supervised by a humanity faculty member and an ECE faculty member (the contact person for this job post).

More details about the opening including the application link can be found here: https://jobs.ncsu.edu/postings/152789

If you have any questions, please don't hesitate to let me know. I also highly appreciate it if you could forward this opening to relevant parties.

About us

GE Healthcare is a leading global medical technology and digital solutions innovator. Our mission is to improve lives in the moments that matter. Unlock your ambition, turn ideas into world-changing realities, and join an organization where every voice makes a difference, and every difference builds a healthier world.

Responsibilities

• You will play a crucial role in translating clinical feedback into innovative ideas and finally software solutions for ultrasound image formation.
• The role requires a focus on the early stages of product development, such as scientific feasibility studies or algorithm development in the field of medical ultrasound beamforming.
• This role will entail interacting with groups such as systems engineering and clinical product management, in addition to internal and external academic and industrial R&D partners.
• You will also develop the architecture and specifications for our next generation ultrasound systems. You will evaluate the latest research on ultrasound imaging with respect to its clinical relevance and implementation possibilities.

Qualifications

• You have a master’s degree in electrical engineering, physics, biomedical engineering or a related field significant experience, or a PhD relevant experience in the relevant fields.
• You have a deep proven technical experience in ultrasound imaging, in particular beamforming.
• You have experience in applying deep learning methods in the ultrasound processing chain.
• You have a deep understanding of ultrasound physics, especially wave propagation.
• You have designed, implemented, and tested innovative signal and image processing algorithms for ultrasound imaging.
• You have performed ultrasound experiments and acquired data in complex set-ups.

About us

GE Healthcare is a leading global medical technology and digital solutions innovator. Our mission is to improve lives in the moments that matter. Unlock your ambition, turn ideas into world-changing realities, and join an organization where every voice makes a difference, and every difference builds a healthier world.

Responsibilities

• The role requires a focus on the understanding of product lifecycle, conduct scientific feasibility studies or algorithm development in the field of system analytics, employing state of the are data science concepts and machine learning algorithms.
• This role will entail interacting with service teams, clinical product management addition to external academic and industrial partners to develop systems and strategies for analyzing and identifying system areas to improve performance, reliability, and customer workflows.
• You will also participate in the development of the architecture and specifications for our next generation ultrasound systems.
• If you are a communicative and assertive team player who enjoys realizing innovative ideas as part of a dynamic team, then you are the right person for us.

Qualifications

• Master’s degree in computer science, electrical engineering, mathematics, physics, biomedical engineering or a related field relevant work experience, or a PhD in the relevant fields.
• Deep proven experience in data science, ideally with focus on pattern recognition, data analytics and machine learning, applied to system performance
• Experience in assembling large, complex data sets that meet functional / non-functional business requirements.
• Strong analytic skills related to working with both structured and unstructured datasets.
• An excellent working ability in languages such as R, Python, MATLAB is expected.
• Experience of working with a wide variety of data sources using technology such as SQL and AWS ‘big data’ technologies.
• A very good standard of written and spoken English is essential for this position.

We conduct research on state-of-the-art deep generative models that are used to enable real-world Bosch systems to be data-efficient and safe. We are looking for a research scientist to support us both in academic research activities and in transferring those results to real-world systems.

The goal of this position is to work on problems such as developing new learning algorithms for generating better training datasets, making algorithms robust, reliable, and safe when learning even from limited/biased datasets, understanding where the models fail, and investigating algorithms for online adaptation in a self-supervised manner. This includes work on (but not limited to):

- Use of generative models for data augmentation: generation of synthetic data using both computer graphics and image-synthesis with generative models (i.e., VAE, GANs, diffusion models), as well as techniques for domain transfer.
- Adversarial learning for data augmentation, robust training, and imbalance learning.
- Continual learning.

Concretely, your tasks will include:

- Develop and implement novel approaches for smart data generation and augmentation using deep generative models and computer graphics techniques, publish results at top-tier AI venues, and apply them on real-world problems.
- Coordinate with customers to ensure our research/methods fit their problems, support the transfer from research prototypes into products.
- Supervise PhD students and support collaborations with academic partners.
- Support the acquisition of publicly funded projects.

We have a vacancy for a PhD candidate in “Interactive visualization of spectral images in a museum setting” at the Department of Computer Science in Gjøvik. The appointment has a duration of 4 years with with 25% teaching duties in agreement with the department.

Hyperspectral imaging (HSI) is a technology that was initially developed for earth observation, but recently has been exploited for various fields, including art and conservation. Despite being a complex technology, HSI has clear advantages in science communication. It generates images, thus providing readily available visual materials. Furthermore, HSI images cover information human eyes simply cannot see, which means a great potential for creating an engaging and interactive visualization. The target of visualization application is a museum setting. This is a unique project aiming to advance the scientific communication of spectral imaging research by incorporating graphic design principles, and with a team of supervisors from complementary expertise, i.e., spectral imaging, interaction design, and conservation science.

The PhD candidate will focus on developing an interactive visualization for spectral images for stakeholders in a museum setting, for example conservators or museum visitors. Graphic design principles will be adopted in the creation of the visualization, facilitated by experts from the Department of Design, NTNU. As part of the creation of the visualization, research in relevant spectral imaging topic for art and conservation will be conducted, and to be identified based on the area of visualization application.

Required selection criteria

• You must have a professionally relevant background in computer science, image processing, imaging science, and/or related computing disciplines.
• Your education must correspond to a five-year Norwegian degree programme, where 120 credits are obtained at master's level.
• You must have a strong academic background from your previous studies and an average grade from the master's degree program, or equivalent education, which is equal to B or better compared with NTNU's grading scale. If you do not have letter grades from previous studies, you must have an equally good academic basis. If you have a weaker grade background, you may be assessed if you can document that you are particularly suitable for a PhD education.
• You must meet the requirements for admission to the faculty's doctoral program.
• Excellent communication skills.
• A documented good written and English language skills.
• Good programming skills.
• Experience with image/ signal processing.

Preferred selection criteria

• Experience in Python programming language.
• Knowledge or interest in interaction design.
• Norwegian language skill is a plus.

Personal characteristics

• High motivation for research work.
• Well organized.
• Ability to work independently.
• Ability to work both individually and in a (virtual) team environment with a high level of personal responsibility and initiative.
• Flexibility and ability to take direction and accommodate feedback from diverse stakeholders.
• Ability to meet deadlines and produce work of a consistently high standard.
• Eager to disseminate research results through publications and presentations at international conferences, and through other venues of scientific communication.
• Ability to think and code creatively and outside the box.

Deadline: 15th May 2022
Application portal: https://www.jobbnorge.no/en/available-jobs/job/225341/phd-candidate-in-interactive-visualization-of-spectral-images-in-a-museum-setting

Houston Learning Algorithms Lab is looking for strong Ph.D. candidates interested in conducting research at the nexus of artificial intelligence and medical imaging. Ideal candidates should meet the following criteria:

* Good mathematical background
* Solid programming skills (Python, Java, C++, etc.)
* Strong passion for research
* Experience with advanced topics (optimization theory, statistical inference, etc.) is a plus
* Experience with database, web development, and cloud computing is a plus

Please send your CV, transcripts, and personal statement to hvnguy35@central.uh.edu to apply.

Applications are invited for a funded Ph.D. position in deep learning for applications in visual recognition. The candidate will work under the supervision of Prof. Granger at the Laboratory of imaging, vision and artificial intelligence (LIVIA), Dept. of Systems Engineering at ETS Montreal. This fully-funded position is available immediately, for a duration of 4 years, and offers a competitive salary exempt from taxes. It also offers a possibility for collaborations-internships with top R&D companies and institutions in Montreal and abroad.

We are looking for a highly motivated doctoral student who is interested in performing cutting-edge research on machine learning models applied to visual object recognition, with a particular focus on deep learning architectures (e.g, auto-encoders, convolutional and recurrent neural networks), domain adaptation, multimodal and spatiotemporal fusion, and weakly-supervised learning. Application areas include, for example, emotion recognition in health monitoring, object localization and segmentation in medical image analysis, and person re-identification in video surveillance.

Prospective applicants should have the following profile:
• strong academic record with an excellent M.Sc. degree in computer science, applied mathematics, or electrical engineering, preferably with expertise in one or more of the following areas: machine learning, computer vision, pattern recognition, artificial intelligence;
• good mathematical background;
• Excellent written and verbal communication skills in English;
• good programming skills in languages such as C, C++, and Python, with knowledge of deep learning frameworks (e.g., Pytorch);
• publication in one of the major conferences or journals in computer vision and machine learning would be an asset.

Application process:
For consideration, please send your CV, names and contact details of two references, transcripts, a link to an M.Sc. thesis, as well as relevant publications to: eric.granger@etsmtl.ca

Eric Granger, ing., Ph.D.
Professor and Director of the LIVIA
FRSQ Double Chaire in AI and Digital Health
Department of Systems Engineering
École de technologie supérieure
Université du Québec
1-514-396-8650
eric.granger@etsmtl.ca

The research team at the Bosch Center for Artificial Intelligence (BCAI) provides the opportunity for candidates currently enrolled as PhD students in machine learning, computer science, or a related field to perform an 'industry sabbatical' for 3-12 months. At BCAI we build the foundation to generate real-world impact through cutting-edge research focusing on safe, secure, robust, and explainable AI. We design and implement AI for smart, connected, and autonomous technologies across Bosch business sectors. During the internship you will get the chance to develop and implement novel algorithms, and evaluate them on multi-modal open and Bosch datasets. Together with BCAI researchers you will perform original research, theoretical investigations, and aim to publish at top conferences. The goal is to define the topic in such a way that it is closely related to your PhD topic.

Possible research areas include, but are not limited to:

◾ Use of generative models for data augmentation: generation of synthetic data using both computer graphics and image-synthesis with generative models (i.e., VAE, GANs, diffusion models), as well as techniques for domain transfer.
◾ Adversarial learning for data augmentation, robust training, and imbalance learning.
◾ Continual learning.

OPPO U.S. Research Center is looking for a Senior Research Engineer to join our AI Research Team. You will be working on developing video understanding algorithms for mobile/embedded devices. The ideal candidate will have a keen interest in producing new science to understand intelligence and transfer technologies into products for better serving our hundreds of millions of users.

Duties and responsibilities
Develop algorithms and incubate products in the fields of video understanding related topics for mobile/embedded devices
Work towards long-term ambitious research goals, while identifying intermediate milestones that can be applied to product development
Collaborate with software engineering experts to build shipping industrial-strength codes

Basic Qualifications
PhD degree in Computer Science or related engineering field
Tracked record of developing demanding deep learning algorithms and applications
Research experience in developing deep learning algorithms for video understanding related topics
Familiar with at least one of the deep learning frameworks such as TensorFlow and PyTorch
Strong programming and debugging skills in Python/C++
Ability to work independently and collaboratively in multi-functional teams
Strong foundation in computer vision, machine learning, deep learning etc

The Navy Center for Applied Research in Artificial Intelligence
(NCARAI) at the Naval Research Laboratory (NRL) in Washington DC is looking for 1-2 postdocs to join our team. Our team is multidisciplinaryIncluding individuals with a range of expertise from machine learning to robotics and cognitive science.

Our lab's focus is primarily on human robot interaction, and we seek individuals who are interested in working to solve related perception and machine learning problems. Specifically, we are looking for people interested in:

• Object detection and recognition, particularly few-shot learning on robotics platforms
• Spiking neural networks, neuromorphic computing, and perceiving and understanding visual and motion cues
• Biometric person identification using multispectral cues

We will consider applicants with either background in these areas or an interest to learn. An open mind, an ability to work well in medium size groups, and a strong publishing record are all required.

Our postdoc deadline is rolling, please contact me
(ed.lawson@nrl.navy.mil) if you are interested.

You must be a US citizen to apply for this position.

Responsibility:
1. Lead the image processing algorithm development for all media products widely.
2. Design, develop and implement machine learning algorithm and hardware especially based on Deep Neural Network for
• ISP(Image Signal Processor)
• Image recognition, understanding
3. Design and develop an advanced image processing and computer vision system for mobile and/or wearable devices.
4. Investigate and analyse innovative technologies.
5. May participate in development of intellectual property.
6. May coordinate inter-departmental activities and researches.
Requirement:
1. BS/MS/PhD degree in Computer Science, Electronic Engineering, or similar majors.
2. Professional experience in modelling/training/deploying deep neural network (DNN). Highly valued is experience in developing DNN for use in image processing on mobile devices. Experience in projects that employ Caffe and/or Tensorflow.
3. Work experience in developing ISP (Image Signal Processor), Camera DSP SDK, display system architecture and algorithms, image quality improvement, DTV, Display Driver IC. Highly valued is experience in mobile device development.
4. Advanced programming skills in C/C++, Python, and Matlab. Optional: LSI design experience (Verilog or RTL).
5. Industry background:
I. Work experience in developing cameras and/or digital media products.
II. Leading role in image processing, photography, computer vision projects.
III. Leading role in display image enhancement system design, display image processing projects.
6. Additional skills required
I. Fluent English (written & verbal) are required, Japanese and Chinese is a strong plus.
II. Excellent interpersonal, written, and oral communication skills.
III. Short-term stay in China based on request.

An opening is now available for a postdoctoral researcher in the department of medical physics for individuals interested in medical image analysis combining deep learning research. The two-year project will focus on the development of advanced deep learning and machine learning classifiers to early predict toxicity to radiation treatments and track cancer response from longitudinal images and develop deep learning methods to analyze novel flow-cytometry and histopathological images. This is an excellent opportunity for a researcher with a PhD in biomedical engineering, computer vision, medical physics, or computer science background interested in working on real problems for improving cancer treatments while advancing their skills in medical image analysis and work on highly novel and large datasets. The job will involve working with a multi-disciplinary team of computer scientists, medical physicists, radiation oncologists, and pathologists.

Ideal candidates must have a strong programming background (Python and Matlab) and be familiar with deep learning libraries (e.g. Pytorch/Keras). Knowledge of machine learning and/or computer vision is required. Prior experience in analyzing medical images and/or radiomics analysis is highly desirable. Excellent written and communication skills is required. Successful completion of the project is expected to result in one or more high quality technical publications.

Memorial Sloan Kettering Cancer Center is located on the Upper East Side of Manhattan, and is recognized as a world leader in clinical cancer care and research. Interested candidates should send a resume and list of three references via e-mail to:

Harini Veeraraghavan, Ph.D.
Associate attending computer scientist
Department of Medical Physics
Memorial Sloan Kettering Cancer Center
1275 York Ave.
New York, NY 10065
e-mail: veerarah at mskcc.org

Senior Data Scientist at Argo AI
Pittsburgh, PA

Who we are:

Argo AI is a global self-driving products and services company on a mission to make the world’s streets and roadways safe, accessible, and useful for all. Our technology is built to enable commercial services for autonomous delivery and ridesharing in cities.

With experienced leaders in the field and collaborative partnerships with some of the world’s top consumer brands, we’re working block by block, city by city to empower people and businesses to be more successful. We’re individuals driven by strong values to solve complex problems together. Come join us to reimagine the human journey.

Meet the team:

The Data Science team is providing data exploration and analysis for the entire organization including Testing Operations, Hardware, Software, Management, and Product teams. We analyze data needed to provide actionable insights, draw conclusions from the data, and support data driven decision making at Argo AI. We are hiring experienced Data Scientists to work in high visibility roles that provide the opportunity to learn about, interact with, and add significant value to every part of our company.

What you’ll do:

Collaborate with stakeholders to identify their needs and provide data-driven solutions

Apply statistical methods to support high-quality and meaningful data analyses

Leverage data to drive and optimize engineering processes at Argo AI

Help define and promote Data Science strategy and best practices

Work with modern cloud, big data, and analytics technologies

Own initiatives from inception to implementation

What you'll need to succeed:

Degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field

At least 3-years of relevant working experiences as a Data Scientist

Significant experience applying statistical methods to data analysis and modeling. This includes construction of confidence intervals, prediction intervals, and advanced regression analyses

Understanding of engineering and testing processes in autonomous driving development is a plus

Experience working with SQL and NoSQL database technologies

Experience working with Data Warehouses like Redshift, BigQuery, or Snowflake

Proficiency analyzing data with Python (or R)

Strong team player that can collaborate effectively with customers and other teams

Strong presentation and communication skills

What we offer you:

High-quality individual and family medical, dental, and vision insurance
Competitive compensation packages

Employer-matched 401(k) retirement plan with immediate vesting

Employer-paid group term life insurance and the option to elect voluntary life insurance

Paid parental leave

Paid medical leave

Unlimited vacation

Complimentary daily lunches, beverages, and snacks

Pre-tax commuter benefits

Monthly wellness stipend

Professional development reimbursement

Employee assistance program

Discounted programs that include legal services, identity theft protection, pet insurance, and more

Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Our Background:

Argo AI was founded in 2016 by industry experts with extensive experience building robotic systems for commercial applications. Our once-small team has since grown into an over 1,700-person strong company with strategic partnerships with some of the world’s leading consumer brands. With global headquarters in Pittsburgh, we operate in eight cities across the U.S. and Germany in areas where self-driving technology can have the biggest impact on improving safety, traffic, and transportation equity.

At Argo AI, we believe that embracing differences delivers superior results. We are an equal opportunity employer that is committed to an inclusive environment for all employees.

To ensure the health and well being of our teammates and partners, Argo is working toward a policy that requires those working on site to be fully vaccinated against COVID-19. The amount of on-site work required for each role will vary based on the essential functions of the position and designations made by team leaders. Whenever possible, we try to consider special circumstances and provide flexibility for some remote work.

This role is designated as one that requires frequent on-site work. Candidates should expect to come into the workplace 5 days per week. A COVID-19 vaccination is required to come on site. Argo will consider accommodations for disability and religious-based reasons or as otherwise required by applicable law.

About the role:

As a Computer Vision Engineer, you will work on Kaiko’s ML data framework, developing and deploying machine-learning models and image analysis pipelines to extract insights from medical images.

Given access to clinical healthcare data at scale, you will work closely with software and medical professionals, to understand the data, formulate projects to address unmet clinical need, and build software for automated image analysis solutions.

How you’ll contribute:

• Work at the intersection of machine learning research, software engineering and multimodal petascale+ data
• Develop and apply computer vision models / pipelines / software for medical image analysis
• Interact with clinical / scientific experts to identify and define projects, and to present results to key stakeholders
• Acquire detailed understanding of particular types of medical images and diseases in a clinical context
• Implement processes for the ground-truth labelling of image data
• Develop software and workflows that support a long-term vision for ML research and production, including developing Kaiko’s ML data framework and internal tools for medical image data
• Monitor academic research and maintain state-of-the-art knowledge of emerging trends and developments
• Maintain expert knowledge of available tooling for particular modalities and how to integrate it into pipelines
• Build for significant growth and scaling challenges – achieving a high degree of robustness and performance
• Enable data driven science discoveries in biology and healthcare

What you’ll bring:

• Ph.D. in a related area, or M.Sc. + relevant experience
• Expert knowledge of computer vision, both classical image processing, and relevant Deep Learning architectures and frameworks (TensorFlow / PyTorch) - especially semantic / instance / panoptic segmentation
• Past record of achievement in medical image analysis, or other areas of computer vision – either academic and/or professional
• Awareness of latest developments in academic research - and in the open-source community
• Sharp coding skills in Python and other programming languages
• Willingness to write clean readable code in a modern development environment, supported by test-cases, documentation, deployment pipelines
• Good general knowledge of the foundations of machine learning and data science
• Confident Linux user, as needed
• Fluent professional-level English, and polished communication and interpersonal skills
• A sense of technical curiosity and adventure around applying machine learning in healthcare!

Nice to haves:

• Experience with image modalities like digital pathology (whole slide images), radiology (CT, MRI, PET), etc.
• Knowledge and prior experience in healthcare and/or computational biology
• Experience productizing ML solutions and related MLOps
• Scala / C++ / Java – and modern software engineering (object-oriented, functional programming) and CI/CD
• Knowledge of Spark or other frameworks for processing data at scale
• Knowledge of cloud-based computing environments: e.g. Azure/AWS

About the Role
We are looking for a Senior Perception Engineer for vehicle automation, autonomy, and machine coordination. Trimble has long been a leader in precision self-steering semi-autonomous vehicle systems and is continuing to lead in developing innovative and intelligent vehicle automation solutions. This role will be critical to developing market-leading products and solutions; working closely with systems engineers, UI, software and firmware engineers, hardware engineers, test engineers, and product marketing.
At Trimble, we help you build a career with purpose. Working with us means you get to tackle some of the world's biggest challenges, making your mark with cutting-edge technologies, alongside brilliant colleagues, in a place where we all belong.

What You Will Do:
Design and develop perception system software components for functionally safe autonomous vehicles.
Use Mathworks toolchain (Matlab, Simulink, Stateflow etc) for model-based design (MBD) of safety critical software components, where applicable.
Integrate C/C++ software features or libraries developed by research teams into the functional safety architecture.
Ensure the software meets MISRA compliance.
Participate in formal design, code reviews, etc. to ensure quality software
Help develop the unit and integration tests for the software modules, as well as the functional safety system tests for the perception system
Exposure to functional safety activities (HARA, FMEDA, FMEA, FTA etc.) in the context of the perception system development.

What We are Looking For:
Software Engineering, computer science, or similar degree
Algorithm Development with C/C++
Experienced in one or more of the following areas: perception sensor processing algorithms, developing systems to a well defined process, an international standard, or with an independent certification body.

TRIMBLE’S INCLUSIVENESS COMMITMENT
We believe in celebrating our differences. That is why our diversity is our strength. To us that means actively participating in opportunities to be inclusive. Diversity, Equity, and Inclusion has guided our current success while also moving our desire to improve. We actively seek to add members to our community who represent our customers and the places we live and work.
We have programs in place to make sure our people are seen, heard, and welcomed and most importantly that they know they belong, no matter who they are or where they are coming from.

Saarland University is one of the leading locations for computer science in Germany and Europe. The newly to be established research group on computer vision and machine perception will be headed by Eddy Ilg and has two open positions for PhD students in computer vision and continual learning. Please see https://cvmp.cs.uni-saarland.de.

While machine learning is omnipresent, a strong limitation of conventional machine learning systems is that they are trained on fixed datasets and not able to adapt. The goal of your PhD will be to create state-of-the-art 2D and 3D machine perception algorithms that can learn incrementally and evolve. This is a topic that is highly relevant for the future of AI and connects to 2D and 3D vision, natural language processing, reinforcement learning and fundamental research. You will be working in an interdisciplinary setting embedded in the environment of Saarland Informatics Campus, working with leading researchers in the field and building international relationships.

Requirements:

• An outstanding Bachelor’s or Master’s degree
• Coursework in computer vision and machine learning
• A thesis in a related topic
• Strong interest in research
• A previously published paper is desired

Please include the following information with your application:

• Your CV
• A recent grade transcript
• A link to your thesis

And send the application to ilg at cvmp.cs.uni-saarland.de.

You can find more information and news at cvmp.cs.uni-saarland.de. Eddy Ilg is known for his contributions to computer vision on optical flow and his work on AR technology at Meta. Saarland University is surrounded by the Saarland Informatics Campus with five strong research institutes and three collaborating university departments. It offers a dynamic and stimulating research environment and holds 28 ERC Grants and 7 Gottfried Wilhelm Leibniz Prize winners. You will be working in an english-speaking diverse environment with international students and collaborate with many other famous professors, inside Saarland Informatics Campus as well as internationally. Industry collaborations with US tech companies are also planned.

Please share this post!

#phd #phdposition #phdstudent #postdoc #machinelearning #deeplearning #computervision #machineperception
#artificialintelligence #computergraphics #saarlanduniversity #saarlandinformaticscampus #hiring #research
#ai #technology #university #augmentedreality

Saarland University is one of the leading locations for computer science in Germany and Europe. The newly to be established research group on computer vision and machine perception will be headed by Eddy Ilg and has an open PostDoc position in computer vision and continual learning. Please see https://cvmp.cs.uni-saarland.de.

While machine learning is omnipresent, a strong limitation of conventional machine learning systems is that they are trained on fixed datasets and not able to adapt. Although continual learning addresses this shortcoming, it is still in an early stage and not yet well established in computer vision. The group is looking for a PostDoc that will lead the effort to advance 2D and 3D machine perception algorithms to be able to learn incrementally and evolve, which is highly relevant for the future of AI. You will be working in an interdisciplinary setting between computer vision, 3D reconstruction, NLP and fundamental machine learning. You will be co-supervising PhD students, contributing to the direction of the group and supporting the group in building international relationships.

Requirements:

• A background in continual learning
• An outstanding PhD with visibility on top-tier conferences
• Interest to work in an interdisciplinary setting in 2D/3D computer vision, NLP and reinforcement learning
• Interest to build international relationships

Please include the following information with your application:

• Your CV
• Your publication list
• A link to your PhD thesis

And send the application to ilg at cvmp.cs.uni-saarland.de.

You can find more information and news at cvmp.cs.uni-saarland.de. Eddy Ilg is known for his contributions to computer vision on optical flow and his work on AR technology at Meta. Saarland University is surrounded by the Saarland Informatics Campus with five strong research institutes and three collaborating university departments. It offers a dynamic and stimulating research environment and holds 28 ERC Grants and 7 Gottfried Wilhelm Leibniz Prize winners. You will be working in an english-speaking diverse environment with international students and collaborate with many other famous professors, inside Saarland Informatics Campus as well as internationally. Industry collaborations with US tech companies are also planned.

Please share this post!

#phd #phdposition #phdstudent #postdoc #machinelearning #deeplearning #computervision #machineperception
#artificialintelligence #computergraphics #saarlanduniversity #saarlandinformaticscampus #hiring #research
#ai #technology #university #augmentedreality

Job summary
Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization.
We’re working on the future. If you are seeking an iterative fast-paced environment where you can drive innovation, apply state-of-the-art technologies to solve real world delivery challenges, and provide visible benefit to customers, this is your opportunity. Come work on the Amazon Prime Air Team!

We're looking for an outstanding Applied Scientist with a focus on Computer Vision and Computer Graphics who will be working on visual sensor simulation to verify and improve Prime Air's onboard perception software stack.

Key job responsibilities
You will be working with a state-of-the-art rendering engine to create large-scale 3D digital twins of the real world and model physical image formation processes of visual sensors to support requirements from Computer Vision / Machine Learning / Perception scientists.

Basic Qualifications

• PhD plus 5+ years of experience in Computer Vision, Computer Graphics or related field
• Graduate from an accredited college or university
• Experience in applied computer vision research
• Experience with render engines
• Proficient in C++ and Python coding skills
• Excellent problem-solving ability

Preferred Qualifications

• Experience building complex software/hardware mission-critical systems that have been successfully delivered to customers at scale
• Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes and testing
• Demonstrated business communication skills
• Experience communicating with various teams to collect requirements, describe product features and technical designs

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Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

Qualcomm's Multimedia R&D and Standards Group are seeking passionate candidates for its Computer Vision team. The team develops advanced AI and deep learning algorithms, architectures, and systems for computer vision applications, enriching the embedded systems for Mobile, XR (VR/AR/MR), Automotive, and IoT products.

The candidates should bring a deep understanding of computer vision, exhibit excellent analytical and algorithm development skills, and proficiency in Python and C/C++ programming. The selected candidate will work in a cross-departmental collaborative environment, and along with other team members, will have responsibilities in one or more of the following areas:
• Research and develop power-efficient deep learning architectures and models in computer vision for AI-enabled camera, video, augmented and virtual reality, including but not limited to object detection and tracking, natural image and video segmentation and analysis, and activity and event recognition.
• Prototype solutions on mobile platforms for proof of concept and demonstration purposes, such as model quantization, C/C++ simulation implementation.
• Support product teams for commercialization, such as solution optimization, performance profiling, and benchmarking.

The Image and Signal Processing (ISP) group at the University of València (Spain) is looking for a motivated postdoc in the intersection of machine learning, computer vision and Earth sciences.

The postdoc position is fully funded by the European Space Agency (ESA) project "DeepExtremes -- AI4Science: Multi-Hazards, Compounds and Cascade events".

-- Brief description --
Climate extremes are on the rise. This is one of the most critical manifestations of climate change as extreme events have multiple impacts: from declining ecosystem functioning associated with reduced ecosystem services e.g., carbon sequestration and water retention, to harvest failure with very direct impacts on human wellbeing. In the last few years, it has been recognized that the highest threats to ecosystems and societies are due to multi-hazard events. Such events may translate into “compound events”, which often do not only affect one particular land-surface process but rather induce entire cascades of consequences. In the project we will rely on deep learning to deal with spatio-temporal data, techniques from computer vision for forecasting impacts, and the advanced regression methods for associating impacts on the biosphere and society. Understanding what the DL models have learned is of importance here, so experience on explainable AI (XAI) techniques and methods from modern Bayesian inference (Bayesian deep learning and deep GP regression) to perform uncertainty quantification, automatic variable relevance determination, and error propagation are pluses.

-- Profile --
- Experience in machine learning, deep learning, image processing, statistics, Bayesian inference
- We love interdisciplinarity! Interested in remote sensing, Earth sciences, climate science
- Experienced in scientific interpretation and analysis of data
- Experienced with or convincing motivation to enter a leadership position
- Familiar with modelling, model-data-fusion and machine learning
- Excellent quantitative skills (e.g. data analysis, modelling)
- Strong programming skills in Python/Julia/R
- Proven record of scientific publications in international peer-reviewed journals
- PhD in maths, physics, or computer science
- Critical and organized sense for data analysis
- Maturity and commitment
- Strong communication, presentation and writing skills are a big plus
- Collaborative team player

-- Your tasks --
- Lead research and development in the project activities
- Responsibility to deliver and report
- Collaborate and coordinate a team of researchers
- Not mandatory, but possibly to co-advise a PhD student
- Publish in international peer-reviewed journals and conference venues

A two-year postdoc position is open in the research axis “Vision and 3D Perception for Scene Understanding” of a joint Valeo / Inria context. The candidate will be colocated in the two institutes that are both located in central Paris.

Starting date is September 2022 (approximative).

Scientific context

In the same way that learning with transformers has somehow brought a revolution in natural language processing [Vas17], and then in image processing [Car20, Dos21], recently emerging transformers [Guo21, Zha21] for point clouds are now also starting to significantly boost the performance of 3D processing. Yet, the general concepts of transformers and the reasons for their success are not fully understood, and there are still many open ways to adapt them efficiently to 3D.

Topics

In the same way that learning with transformers has somehow brought a revolution in natural language processing [Vas17], and then in image processing [Car20, Dos21], recently emerging transformers [Guo21, Zha21] for point clouds are now also starting to significantly boost the performance of 3D processing. Yet, the general concepts of transformers and the reasons for their success are not fully understood, and there are still many open ways to adapt them efficiently to 3D.

The emergence of transformers opens a wide field of research subjects that matches well with the research axis “Vision and 3D Perception for Scene Understanding”. The goal of this postdoc is to attack some of them.

• A first objective is to investigate the specificity of transformers for 3D. It includes the question of positional encoding, which is widely different in 3D from the 1D (text) and 2D (image) perspectives. It also includes the square complexity issues with cross- and self-attention, taking into account the sparsity of point clouds. More generally, it concerns as well the time and space complexity of point cloud processing, in the perspective of real-time, embedded software.

  This study of 3D transformers will be made through downstream tasks that include object detection, semantic or panoptic segmentation, and denser depth predictions, which are key tasks for autonomous driving. We will study in particular the impact of the specific sparsity and data patterns induced by vehicle sensors. We will also consider a stream of point clouds, as available from a lidar, taking time into account in a 4D perspective.

• Besides, we will investigate the use of transformers backbones regarding self-supervision [Sim21], which is a key approach to bring supervised learning to a new level by saving the cost of annotating large datasets. We will study new pretext tasks in 3D that transformers more specifically leverage, as well as contrastive learning techniques that are tightly linked to the attention mechanism of transformers.

  A PhD student is about to start on self-supervision for 3D at Valeo and another works on 2D supervision for 3D at Inria, though none of them focusing on transformers. The postdoc will be able to work jointly with either PhD student on self-supervision issues.

• Moreover, we will study the transferability of learned transformer models in the perspective of domain adaptation [Vu19a, Vu19b]. In particular, we will investigate the disentangling of latent space representations, working towards domain-invariant features by enforcing orthogonality of the domain features while enabling the discovery of exclusive task or domain features, through their realization via multi-head attention.

  Another PhD student in Valeo is about to start working on 3D domain adaptation, although with a different perspective (using optimal transport). There will nonetheless be a number of collaboration opportunities between this PhD student and the postdoc regarding adapting transformer-based features.

• A last research direction concerns multi-modality, when lidar point clouds are acquired together with camera images, to leverage the similarity and complementarity of sensor information [Jar20]. One technical subject concerns a possible interplay between the forms of transformer attention used in 2D and the kinds of attention that are and will be developed in 3D. Another more general question is the joint self-supervision from the interaction of 2D and 3D, or from cross-task representations. Last, we will study the intertwined relation of geometry and semantics through the semantic scene completion task [Rol20, Rol21].

Profile

Applicants should have defended or be finishing their PhD and have a strong publications record. They should have a solid background in computer vision (including 3D processing) and machine learning, particularly in deep learning, with strong PyTorch coding skills.

To apply

To apply, applicants should preferably send a mail to Renaud Marlet (renaud[dot]marlet[arobasesign]valeo(dot)com) and Raoul de Charette (raoul[dot]de-charette[arobasesign]inria(dot)fr) with:

• a cover letter explaining their interest and adequacy for the postdoc topic,
• their CV/resume,
• possibly, references or recommendation letters.

Application deadline: May 20th, 2022

• Postdoctoral Research Fellow position
• Visiting Research Fellow position

Machine & Hybrid Intelligence Lab is seeking highly motivated postdoctoral fellows (with track record of productivity) on machine learning based medical image analysis problems on NIH R01 projects at the department of radiology, Northwestern University.

We are particularly interested in developing
(a) explainable machine learning algorithms for high-risk applications, and
(b) human-in-the-loop hybrid intelligence methods for computer aided diagnosis systems.

We welcome all applicants with Ph.D. degrees with background in machine learning/deep learning and their applications in medical image analysis. The duration of the fellowship is 2-years and can be extended based on availability of the funds. We also welcome visiting research fellows with their own funding.

The department of radiology is dedicated to attracting current and future leaders of imaging sciences through our excellence in research and collaborative enterprise. The radiology department is located in downtown Chicago, IL.

Start Date: Immediately
Close Date: Until filled.

If interested, please send a CV and one page research plan / experience to Prof. Bagci
ulas.bagci@northwestern.edu

We are looking for passionate Research Engineers/Applied Scientists or PhD Interns to architect, design, research and develop computer vision algorithms and software systems in the areas of 3D Vision and robot SLAM, targeting at camera-based 3D spatial perception and real-time 3D scene understanding.

You will work with a team of world class researchers and engineers to build the next generation of visual perception algorithms and systems to achieve spatial AI in a new product. You will mainly contribute to industry grade algorithms and software development. Working with the team, you will integrate the software components into a fully functional system running real time on a mobile/embedded device. Ideal candidates have a research background in 3D computer vision, or Robot SLAM and/or computer graphics, or neural rendering, video game program, as well as must have strong software engineering and C/C++ programming skills. Experience with camera sensors and real time compute and signal processing hardware (GPU/CUDA/DSP) is a plus. This full time role could be a standard or a senior role, depending on education and past research and employment experience.

Minimum Requirement:
• PhD/MPhil degree program in the field of Computer Science, Electrical Engineering, Robotics, Machine Learning, Mathematics, or equivalent.
• Strong knowledge with Mathematical and numerical optimization, linear algebra, probabilistic estimation, and 3D geometry.
• Strong knowledge in image processing or video or computer graphics, or computer vision or video game development.
• Must publish one or more papers at leading computer vision, or computer graphics, or machine learning, or robotics conferences or journals, such as CVPR, ICCV, ECCV, ACCV, BMVC, WACV, 3DV, SIGGRAPH, ICCP, Neurlps, ICLR, ICRA, IROS, RSS, and ISMAR, or in major CV/ML/CG/Robotics journals.
• 3+ years programming experience in Python and C++, familiar with modern C++ features.
• Experience understanding, developing, and analysing computer vision or deep learning systems.
• Availability to work legally in Australia.
• Proficient English language skills.

About Tencent: Tencent is a world-leading internet and technology company that develops innovative products and services to improve the quality of life of people around the world. Tencent is the world's largest video game company. It also owns and operates QQ and WeChat, and Tencent Music. Tencent is an equal opportunity employer that is committed to inclusion and diversity.

Multiple Job opportunities are available at NORTHWESTERN UNIVERSITY's Machine and Hybrid Intelligence Lab

• Postdoctoral Research Fellow position
• Visiting Research Fellow position

Machine & Hybrid Intelligence Lab is seeking highly motivated postdoctoral fellows (with a track record of productivity) on machine learning-based medical image analysis problems on NIH R01 projects at the department of radiology, Northwestern University.

We are particularly interested in developing
(a) explainable machine learning algorithms for high-risk applications, and
(b) human-in-the-loop hybrid intelligence methods for computer-aided diagnosis systems.

We welcome all applicants with Ph.D. degrees with a background in machine learning/deep learning and their applications in medical image analysis. The duration of the fellowship is 2-years and can be extended based on the availability of the funds. We also welcome visiting research fellows with their own funding.

The department of radiology is dedicated to attracting current and future leaders of imaging sciences through our excellence in research and collaborative enterprise. The radiology department is located in downtown Chicago, IL.

--If interested, please email CV and one page research statement to Prof. Bagci
ulas.bagci@northwestern.edu